I will train yolo detection segmentation ocr ai models
AI,DATA
About this Gig
PROFESSIONAL YOLO & COMPUTER VISION MODEL TRAINING
WHAT I TRAIN:
All YOLO Object Detection:
YOLOv5, v6, v7, v8, v9, v10, YOLO11 (all sizes: n/s/m/l/x)
Segmentation: YOLO-seg, SAM, Mask R-CNN, U-Net
Image Classification: EfficientNet, ResNet, ViT
OCR: PaddleOCR, EasyOCR (Hindi + English + multi-lang)
NVIDIA TAO Toolkit: Jetson/TensorRT 5-10x speedup
WHY ME:
Production-grade models (not toy notebooks)
Auto-labeling with SAM + Grounding DINO (save 80% time)
Detailed mAP/precision/recall reports
Multiple exports: .pt, .onnx, .trt, .tflite, .coreml
FREE retraining if accuracy below target
Response under 1 hour
YOU GET:
- Trained weights + inference script
- Training metrics + graphs
- Confusion matrix + PR curves
- 7-day free support
BEFORE ORDERING, message me with:
1. 5-10 sample images
2. Objects/text to detect
3. Deployment target (cloud/edge/mobile)
Custom quote in 1 HOUR. Let's build!
Programming language:
Python
•
MATLAB
•
SQL
•
MLflow
•
Amazon SageMaker
Frameworks:
Scikit-learn
•
DeepPy
•
SimpleCV
•
PyTorch
•
Panda
FAQ
Do I need to provide labeled data?
Either is fine! Provide labeled data (YOLO/COCO/CVAT format) OR raw images — I'll auto-label using SAM + Grounding DINO for most use cases. Saves you 80% time.
What if model accuracy is low?
FREE retrain if mAP < 70% on test set. Premium tier includes unlimited revisions until you're 100% satisfied. Your money is safe.
Can it run on Raspberry Pi or mobile?
Yes! Premium tier includes TensorRT/CoreML/TFLite exports for edge devices (Jetson Nano, Orin, RPi, Android, iOS). 5-10x faster inference vs vanilla PyTorch.
How many images do I need?
Minimum 50 images/class for object detection. For best results: 200+ per class. For segmentation: 100+ masked images. I'll guide you based on your use case.
Do you sign NDA?
Yes, NDA available on Premium tier and above. Your data and models stay 100% confidential — deleted from my workspace after 30 days unless requested otherwise.

